Description

You will lead end-to-end machine learning projects characterized by high ambiguity, scale, and complexity.

Responsibilities

• Develop novel ML algorithms and indicators for time-series forecasting, specifically for actuarial reserving and affordability programs.
• Implement state-of-the-art machine learning models and rigorously evaluate their performance.
• Communicate algorithm performance and findings across interdisciplinary teams of scientists and engineers.
• Produce internal and external documentation, including publications for machine learning and scientific conferences.
• Drive the research and innovation agenda within the AI team.

Required Skills

• 5+ years of experience in Machine Learning (ML) engineering and development.
• Strong expertise in time-series forecasting prediction techniques.
• Proven track record of developing novel ML algorithms.
• Experience evaluating and validating machine learning model performance.
• Ability to write and publish technical documentation for scientific conferences and journals.
• Experience collaborating effectively within interdisciplinary scientific and engineering teams.

Preferred Skills

• Background in actuarial science or financial modeling applications.
• Published research in machine learning or related scientific fields.

Key Skills

Education

Any Graduate